Index measurement and analysis on spatial-temporal evolution of China's new economy based on the DPSIR model

Wen, Ting; Qi, Sinan; Qian, Yue

doi:10.1016/j.iref.2023.11.010

Cited by 2 publications

(1 citation statement)

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“…The core idea of a Markov chain is to construct a Markov transfer matrix to describe the dynamic evolution of marine green aquaculture efficiency in each province. Specifically, a Markov chain is essentially a random process and satisfies {x(t), t∈T}, where x(t) is any value of finite state space, L, and has a first-order no aftereffect property, and T is the observation period of the study sample [34][35][36]. The variable x has states j and I in periods t and t−1, respectively, and states in other periods are i k (k = 0, 1, .…”

Section: Markov Chainmentioning

confidence: 99%

Study on the Spatial Imbalance and Polarization of Marine Green Aquaculture Efficiency in China

Wang,

Mao,

et al. 2024

Water

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In-depth analyses of the spatial imbalance and polarization of marine green aquaculture efficiency have a profound impact on the realization of high-quality development of fisheries. Based on the data on mariculture in nine coastal provinces of China from 2006 to 2019, this research analyzed the spatial imbalance and polarization of green mariculture efficiency using quantitative measurements and explored their causes. The results showed that (1) the efficiency of marine green aquaculture in China is relatively effective, but there is still room for improvement. The spatial imbalance of the whole country and the three marine economic circles shows an increasing trend, and the efficiency of marine green aquaculture in China has two levels of differentiation characteristics. Compared with the coastal provinces with low and high levels of marine green aquaculture efficiency, the degree of spatial imbalance in the medium-level coastal provinces is greater. In the long run, the efficiency of China’s marine green aquaculture will slowly evolve to a high-level state, and it is particularly important to break the “self-locking trap” of the low-level state. (2) The differences in mariculture yield among coastal provinces are the main factor affecting the spatial imbalance of green mariculture efficiency in China. Promoting the development of low-carbon, resource-saving and high-added-value mariculture products and achieving a win–win situation of economic and ecological benefits is an important means to alleviate the spatial imbalance of China’s mariculture efficiency. (3) There is a certain polarization trend in the efficiency of marine green aquaculture in China, and the polarization degree shows an overall upward trend. Compared with the northern and eastern marine economic circles, the spatial polarization of green aquaculture efficiency in the southern marine economic circle is the lowest. During the observation year, the change in green aquaculture efficiency in coastal provinces did not converge into minority groups, and the main reason for spatial polarization was that there was a large gap in green aquaculture efficiency among coastal provinces. The research results can provide a reference for accelerating the green transformation of mariculture and promoting the high-quality development of fisheries.

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Section: Markov Chainmentioning

confidence: 99%